An integrated approach to function annotation in an enzyme superfamily

Our understanding of function in the protein universe is still far from complete: a recent re-annotation exercise of molecular biology’s favourite model organism Escherichia coli concluded with a third of its possible proteins lacking any clue to function and the situation is much worse for other genomes. Superfamilies – large, functionally divergent groups of homologous proteins – present significant, unresolved challenges to automated genome annotation methods. A prime example is the Histidine Phosphatase (HP) superfamily (Rigden, 2008) which harbours many families of still-uncharacterised function. Even in human beings, important roles are still being discovered for its members (Takeda et al., 2009) adding to crucial functions of other HP sequences in, for example, glucose metabolism by glycolysis and its regulation. Activities of these and other HP enzymes are implicated in important human diseases including cancer. This project will apply an extensive suite of bioinformatic methods to predict new functions for HP enzymes and improve our understanding of the superfamily. The student will harvest information from sources including genome context, domain fusions and phyletic distribution. A principal focus will be exploiting a range of recently-developed structure-based function prediction approaches, employing either modelled or experimental structures (Rigden, 2009). The project may therefore involve the determination of crystal structures for particularly interesting enzymes. Structure-based approaches will include prediction of enzyme specificity using molecular modelling to dock candidate small molecule or peptide substrates. Confirmation of predictions may involve a range of biophysical methods and/or direct enzyme assays. The project offers exciting possibilities to work at the interface between sequence- and structure based protein bioinformatics, chemoinformatics, experimental structural biology and biochemistry.


Training:
The project will provide comprehensive exposure to modern sequence- and structure-based protein function prediction methods. The project also lies at the intersection of bioinformatics, chemoinformatics and molecular modelling, tapping into expertise in Chemistry. Further, the application of X-ray crystallography will provide comprehensive training in the over-production of recombinant proteins, their assay and crystallization and their experimental structure elucidation using state-of-the-art X-ray radiation facilities. The student may also use biophysical methods such as differential scanning fluorimetry (DSF) and isothermal titration calorimetry (ITC) to characterise the interaction of proteins with their predicted substrates. The long-term importance of all of these techniques can only increase.